Clinical Studies, Big Data, and Artificial Intelligence in Nephrology and Transplantation
A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Nephrology & Urology".
Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 96313
Special Issue Editors
Interests: artificial Intelligence; machine learning; meta-analysis; acute kidney injury; clinical nephrology; kidney transplantation
Special Issues, Collections and Topics in MDPI journals
Interests: artificial intelligence; machine Learning; nephrology; acute kidney injury; clinical nephrology; kidney transplantation
Special Issues, Collections and Topics in MDPI journals
Interests: machine learning; kidney transplantation; observational studies; statistical analysis; epidemiology
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In recent years, artificial intelligence has increasingly been playing an essential role in diverse areas in medicine, helping clinicians in patient management. In nephrology and transplantation, artificial intelligence can be utilized to enhance clinical care, such as hemodialysis prescriptions and the follow-up of kidney transplant patients. Furthermore, there are rapidly expanding applications and validations of comprehensive, computerized medical records and related databases, including national registries, health insurance, and drug prescriptions.
In this Special Issue, we are making a call to action to stimulate researchers and clinicians to submit their invaluable works including original clinical research (single- or multi-center), database studies from registries, meta-analyses, and artificial intelligence research in nephrology including acute kidney injury, electrolytes and acid–base, chronic kidney disease, glomerular disease, dialysis, and transplantation that will provide additional knowledge and skills in the field of nephrology and transplantation to improve patient outcomes.
Potential topics include, but are not limited to, the following:
-Artificial intelligence and machine learning for predicting acute kidney injury;
-Machine learning predicting acute kidney injury and renal replacement therapy in intensive care units;
-Re-transplants compared to primary kidney transplants recipients: the OPTN/UNOS database;
-Alcohol use and development of chronic kidney disease: a nationwide database analysis;
-Association of race and poverty with mortality on maintenance dialysis using the United States Renal Data System database;
-Prevention of contrast-induced acute kidney injury in patients undergoing cardiovascular procedures—a meta-analysis;
-Systematic review and meta-analysis of renal replacement therapy modalities for acute kidney injury.
Dr. Wisit Cheungpasitporn
Dr. Charat Thongprayoon
Dr. Wisit Kaewput
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Clinical Medicine is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- artificial intelligence
- machine learning
- systematic review
- meta-analysis
- nephrology
- transplantation
- kidney transplantation
- electrolytes
- acute kidney injury
- chronic kidney disease
- glomerulonephritis
- end-stage kidney disease
- dialysis
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.
Further information on MDPI's Special Issue polices can be found here.